Stephen Wright has been awarded the Khachiyan Prize by the INFORMS Optimization Society. The Khachiyan Prize is the highest honor bestowed by the society and is given to an individual or a team for life-time achievements in the area of optimization. The award recognizes a sustained career of scholarship from nominees who are still active at the year of the nomination.

The citation for Wright states: “For his vast contributions to continuous optimization, spanning theory, algorithms and software, and the impact of his work on control, signal processing, and machine learning.”

Wright is a principal investigator in the MACSER (Multifaceted Mathematics for Rare, High-Impact Events in Complex Energy and Environment Systems) project and is the George B. Dantzig Professor of Computer Sciences at the University of Wisconsin – Madison.

Prior to joining UW-Madison, Wright was a senior computer scientist at Argonne National Laboratory and a professor of computer science at the University of Chicago. He is the author of the widely used book on optimization: “Primal Dual Interior-Point Methods” (SIAM, 1997, with more than 30,000 citations). He was chair of the Mathematical Optimization Society and served as editor-in-chief of Mathematical Programming, Series B. He currently is on the editorial boards of the leading journals in optimization (SIAM Journal on Optimization and Mathematical Programming, Series A) as well as SIAM Review and Advances in Computational Mathematics. He is also a fellow of SIAM and on the SIAM Board of Trustees.

As a member of the MACSER team, Wright has been investigating topics including randomness, adversarial training and both bound-constrained and unconstrained optimization. The MACSER project is led by Argonne National Laboratory and is funded by the U.S. Department of Energy with the goal of exploiting advances in applied mathematics for the solution of complex problems in energy systems.

For information about the Khachiyan Prize, see the INFORMS Optimization website.

For information about MACSER, click here.